§
    cŠtj  ã                  óf   — d dl mZ d dlmZmZ d dlmZ erd dlmZ  G d„ dee         ¦  «        ZdS )é    )Úannotations)ÚTYPE_CHECKINGÚGeneric)ÚSeriesT)ÚNonNestedLiteralc                  ón   — e Zd Zdd„Zdd„Zdd„Zdd
„Zdd„Zdd„Zdd„Z	dd„Z
dd„Zdd„Zdddœdd„ZdS )ÚSeriesListNamespaceÚseriesr   ÚreturnÚNonec                ó   — || _         d S )N)Ú_narwhals_series)Úselfr
   s     úR/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/narwhals/series_list.pyÚ__init__zSeriesListNamespace.__init__   s   € Ø &ˆÔÐÐó    c                óx   — | j                              | j         j        j                             ¦   «         ¦  «        S )aM  Return the number of elements in each list.

        Null values count towards the total.

        Examples:
            >>> import pyarrow as pa
            >>> import narwhals as nw
            >>> s_native = pa.chunked_array([[[1, 2], [3, 4, None], None, []]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.len().to_native()  # doctest: +ELLIPSIS
            <pyarrow.lib.ChunkedArray object at ...>
            [
              [
                2,
                3,
                null,
                0
              ]
            ]
        )r   Ú_with_compliantÚ_compliant_seriesÚlistÚlen©r   s    r   r   zSeriesListNamespace.len   s7   € ð* Ô$×4Ò4ØÔ!Ô3Ô8×<Ò<Ñ>Ô>ñ
ô 
ð 	
r   c                óx   — | j                              | j         j        j                             ¦   «         ¦  «        S )ac  Get the unique/distinct values in the list.

        Null values are included in the result. The order of unique values is not guaranteed.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1, 1, 2], [3, 3, None], None, []])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.unique().to_native()  # doctest: +SKIP
            shape: (4,)
            Series: '' [list[i64]]
            [
               [1, 2]
               [null, 3]
               null
               []
            ]
        )r   r   r   r   Úuniquer   s    r   r   zSeriesListNamespace.unique(   s7   € ð( Ô$×4Ò4ØÔ!Ô3Ô8×?Ò?ÑAÔAñ
ô 
ð 	
r   Úitemr   c                óz   — | j                              | j         j        j                             |¦  «        ¦  «        S )aF  Check if sublists contain the given item.

        Arguments:
            item: Item that will be checked for membership.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1, 2], None, []])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.contains(1).to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (3,)
            Series: '' [bool]
            [
                    true
                    null
                    false
            ]
        )r   r   r   r   Úcontains)r   r   s     r   r   zSeriesListNamespace.contains@   s9   € ð( Ô$×4Ò4ØÔ!Ô3Ô8×AÒAÀ$ÑGÔGñ
ô 
ð 	
r   ÚindexÚintc                ó(  — t          |t          ¦  «        s'dt          |¦  «        j        › d�}t	          |¦  «        ‚|dk     rd|› d�}t          |¦  «        ‚| j                             | j        j        j	         
                    |¦  «        ¦  «        S )a  Return the value by index in each list.

        Negative indices are not accepted.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1, 2], [3, 4, None], [None, 5]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.get(1).to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (3,)
            Series: '' [i64]
            [
                    2
                    4
                    5
            ]
        z'Index must be of type 'int'. Got type 'z
' instead.r   zIndex z8 is out of bounds: should be greater than or equal to 0.)Ú
isinstancer   ÚtypeÚ__name__Ú	TypeErrorÚ
ValueErrorr   r   r   r   Úget)r   r   Úmsgs      r   r&   zSeriesListNamespace.getX   sš   € õ& ˜%¥Ñ%Ô%ð 	!àZ½$¸u¹+¼+Ô:NÐZÐZÐZð õ ˜C‘.”.Ð à�1Š9ˆ9ØZ˜5ÐZÐZÐZˆCÝ˜S‘/”/Ð!àÔ$×4Ò4ØÔ!Ô3Ô8×<Ò<¸UÑCÔCñ
ô 
ð 	
r   c                óx   — | j                              | j         j        j                             ¦   «         ¦  «        S )a×  Compute the min value of the lists in the array.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1], [3, 4, None]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.min().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (2,)
            Series: '' [i64]
            [
                    1
                    3
            ]
        )r   r   r   r   Úminr   s    r   r)   zSeriesListNamespace.miny   ó7   € ð  Ô$×4Ò4ØÔ!Ô3Ô8×<Ò<Ñ>Ô>ñ
ô 
ð 	
r   c                óx   — | j                              | j         j        j                             ¦   «         ¦  «        S )aî  Compute the max value of the lists in the array.

        Examples:
            >>> import pyarrow as pa
            >>> import narwhals as nw
            >>> s_native = pa.chunked_array([[[1], [3, 4, None]]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.max().to_native()  # doctest: +ELLIPSIS
            <pyarrow.lib.ChunkedArray object at ...>
            [
              [
                1,
                4
              ]
            ]
        )r   r   r   r   Úmaxr   s    r   r,   zSeriesListNamespace.max�   s7   € ð" Ô$×4Ò4ØÔ!Ô3Ô8×<Ò<Ñ>Ô>ñ
ô 
ð 	
r   c                óx   — | j                              | j         j        j                             ¦   «         ¦  «        S )aÝ  Compute the mean value of the lists in the array.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1], [3, 4, None]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.mean().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (2,)
            Series: '' [f64]
            [
                    1.0
                    3.5
            ]
        )r   r   r   r   Úmeanr   s    r   r.   zSeriesListNamespace.mean¢   s7   € ð  Ô$×4Ò4ØÔ!Ô3Ô8×=Ò=Ñ?Ô?ñ
ô 
ð 	
r   c                óx   — | j                              | j         j        j                             ¦   «         ¦  «        S )aô  Compute the median value of the lists in the array.

        Examples:
            >>> import pyarrow as pa
            >>> import narwhals as nw
            >>> s_native = pa.chunked_array([[[1], [3, 4, None]]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.median().to_native()  # doctest: +ELLIPSIS
            <pyarrow.lib.ChunkedArray object at ...>
            [
              [
                1,
                3
              ]
            ]
        )r   r   r   r   Úmedianr   s    r   r0   zSeriesListNamespace.median¶   s7   € ð" Ô$×4Ò4ØÔ!Ô3Ô8×?Ò?ÑAÔAñ
ô 
ð 	
r   c                óx   — | j                              | j         j        j                             ¦   «         ¦  «        S )a×  Compute the sum value of the lists in the array.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[1], [3, 4, None]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.sum().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (2,)
            Series: '' [i64]
            [
                    1
                    7
            ]
        )r   r   r   r   Úsumr   s    r   r2   zSeriesListNamespace.sumË   r*   r   F©Ú
descendingÚ
nulls_lastr4   Úboolr5   c               ó~   — | j                              | j         j        j                             ||¬¦  «        ¦  «        S )a^  Sort the lists of the series.

        Arguments:
            descending: Sort in descending order.
            nulls_last: Place null values last.

        Examples:
            >>> import polars as pl
            >>> import narwhals as nw
            >>> s_native = pl.Series([[2, -1, 1], [3, -4, None]])
            >>> s = nw.from_native(s_native, series_only=True)
            >>> s.list.sort().to_native()  # doctest: +NORMALIZE_WHITESPACE
            shape: (2,)
            Series: '' [list[i64]]
            [
                    [-1, 1, 2]
                    [null, -4, 3]
            ]
        r3   )r   r   r   r   Úsort)r   r4   r5   s      r   r8   zSeriesListNamespace.sortß   sE   € ð( Ô$×4Ò4ØÔ!Ô3Ô8×=Ò=Ø%°*ð >ñ ô ñ
ô 
ð 	
r   N)r
   r   r   r   )r   r   )r   r   r   r   )r   r   r   r   )r4   r6   r5   r6   r   r   )r#   Ú
__module__Ú__qualname__r   r   r   r   r&   r)   r,   r.   r0   r2   r8   © r   r   r	   r	      s  € € € € € ð'ð 'ð 'ð 'ð
ð 
ð 
ð 
ð2
ð 
ð 
ð 
ð0
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ð 
ð0
ð 
ð 
ð 
ðB
ð 
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ð(
ð 
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ð*
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ð( */À5ð 
ð 
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r   r	   N)	Ú
__future__r   Útypingr   r   Únarwhals.typingr   r   r	   r;   r   r   ú<module>r?      sž   ðØ "Ð "Ð "Ð "Ð "Ð "à )Ð )Ð )Ð )Ð )Ð )Ð )Ð )à #Ð #Ð #Ð #Ð #Ð #àð 1Ø0Ð0Ð0Ð0Ð0Ð0ðl
ð l
ð l
ð l
ð l
˜' 'Ô*ñ l
ô l
ð l
ð l
ð l
r   